LATENT TREE MODELS: AN APPLICATION AND AN EXTENSION by KIN-MAN POON
نویسندگان
چکیده
xii Chapter
منابع مشابه
Spatial Latent Gaussian Models: Application to House Prices Data in Tehran City
Latent Gaussian models are flexible models that are applied in several statistical applications. When posterior marginals or full conditional distributions in hierarchical Bayesian inference from these models are not available in closed form, Markov chain Monte Carlo methods are implemented. The component dependence of the latent field usually causes increase in computational time and divergenc...
متن کاملAn application of Measurement error evaluation using latent class analysis
Latent class analysis (LCA) is a method of evaluating non sampling errors, especially measurement error in categorical data. Biemer (2011) introduced four latent class modeling approaches: probability model parameterization, log linear model, modified path model, and graphical model using path diagrams. These models are interchangeable. Latent class probability models express l...
متن کاملUsnig LR-Fuzzy Numbers Data to Measure the Eciency and the Malmquist Productivity Index in Data Envelopment Analysis , and Its Application in Insurance Organizations
In many real applications, the data of production processes can't be precisely measured.We develop some fuzzy versions of the classical DEA models (in particular, the CCRmodel) by using some ranking methods based on the comparison of cuts. Our approachescan be seen as an extension of the DEA methodology. The provides users and practitionerswith models which represent some real life processes mo...
متن کاملTrees and Beyond: Exploiting and Improving Tree-structured Graphical Models
Probabilistic models commonly assume that variables are independent of each other conditioned on a subset of other variables. Graphical models provide a powerful framework for encoding such conditional independence structure of a large collection of random variables. A special class of graphical models with significant theoretical and practical importance is the class of tree-structured graphic...
متن کاملExtension of Logic regression to Longitudinal data: Transition Logic Regression
Logic regression is a generalized regression and classification method that is able to make Boolean combinations as new predictive variables from the original binary variables. Logic regression was introduced for case control or cohort study with independent observations. Although in various studies, correlated observations occur due to different reasons, logic regression have not been studi...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2012